Blend, cleanse and prepare data for analytics, reporting or data modernization efforts
Managing big data doesn't always mean hiring more people and buying new tools.
Die EU-Datenschutz-Grundverordnung kommt näher – ausweichen oder draufhalten? In den letzten Wochen hatte ich die tolle Gelegenheit mit zahlreichen Kunden und Partnern über die neue EU-Datenschutz-Grundverordnung (DS-GVO) zu sprechen. Die Meinungen und Erwartungen sind dabei wirklich außerordentlich breit gefächert. Das ist nicht weiter verwunderlich, denn das Thema hat zuletzt stark an
David Loshin explains how to set up a data catalog that will help you get more value from a data lake.
모든 것을 실시간으로 실행하고, 실시간으로 평가하는 바야흐로 ‘스트리밍 시대’입니다. 길을 걷다가 들리는 음악을 그 자리에서 검색하고 스트리밍으로 재생해 듣습니다. 스마트폰 메신저나 소셜 미디어(SNS)를 통해 바로 공유할 수도 있죠. 월드컵과 올림픽 등 스포츠 경기는 물론 대선 토론과 개표 현황 등 정치 이벤트까지 케이블 TV나 페이스북 라이브를 통해 실시간으로 시청합니다. 기업에서는 어떨까요? 매월,
Get on with your day faster by taking a self-service approach to data preparation.
In this blog post I am going to cover the example of importing data into SAS Viya using Cloud Analytic Services (CAS) actions via REST API. For example, you may want to import data into a CASLib via REST API. This means you can perform an import of data outside
Analytics-driven forecasting means more than measuring trend and seasonality. It includes all categories of methods (e.g. exponential smoothing, dynamic regression, ARIMA, ARIMA(X), unobserved component models, and more), including artificial intelligence, but not necessarily deep learning algorithms. That said, deep learning algorithms like neural networks can also be used for demand forecasting,
The Cloud Analytic Server (CAS for short) is SAS’ latest high-performance, scalable, in-memory analytic data server. In this post, I’d like to discuss the CAS physical data model, i.e.what features CAS offers for data storage, and how to use them to maximize performance in CAS (and consequently SAS Visual Analytics
Phil Simon shares his thoughts on this simple yet often-overlooked question.
Niezbędnym elementem wszystkich inicjatyw związanych z przetwarzaniem i analizowaniem danych jest zaufanie do danych, które w znacznej mierze uzależnione jest od ich jakości. Czy można określić jakość danych bez mechanizmów jej monitorowania?
If I’m having a tough week, I might feel sorry for myself for a minute or two. But to snap myself out of it, all I have to do is think of the data managers. Those folks have to contend with duplicate records, bad information, data proliferation, accountability, permissions, privacy,
Joyce Norris-Montanari says focus on data quality and governance, privacy and security when providing data on demand.
West Perth ist das „analytische“ Paradies. Das wissen wir nun dank des Projekts „Paradise Found“ und des Blogbeitrags meines Kollegen Andreas Becks. Klar ist, ohne Machine Learning und Analytics wären wir niemals anhand der untersuchten fünf Millionen Datenpunkte zu 148.233 Orten weltweit aus 1.124 Datenquellen auf den Stadtteil der australischen Boomtown
David Loshin recommends enforcing governed standards to help avoid conflicting analytical results.
When we talk about consent management for the EU’s General Data Protection Regulation (GDPR), one of the key considerations is “consent for a purpose.” It might have been sufficient in the past to provide a form with a single generic consent check box and store the fact that consent was
Jim Harris considers whether we can save private data in the age of big data.
Der Datenschutz macht‘s möglich: Customer Intelligence 360 geht in die nächste Dimension! Der Kunde360, „Omni-Channel“, „Data-driven Marketing“ – wer hat in den letzten zwölf Monat davon gehört? Oder, ich versuche es mal anders rum: Wer hat nicht davon gehört? Ja, richtig – wir sind im Bereich Customer Intelligence/Marketing. Und alles,
Todd Wright says Hadoop can be difficult – but data management can help.
최근 양귀비 불법 재배와 연예인 마약 사건이 잇달아 발생하면서 국내에서는 멀게 느껴졌던 마약 범죄에 대한 관심이 높아지고 있습니다. 실제 관세청은 올해 상반기 마약 밀수가 전년 대비 2.6배 증가했으며, 밀수된 마약의 종류까지 다양해졌다고 발표했는데요. 국가는 이처럼 급증하는 마약 밀수를 차단하기 위해 조사 인력과 장비를 확충하고, 검색 기법을 적극 개발하겠다고 밝혔습니다. 이미
Phil Simon chimes in on the immediacy of enterprise data.
Joyce Norris-Montanari explains why it's so important to pick the right tools to manage your big data.
Wollten Sie schon immer mal an einem Ort leben, wo es kostenlosen öffentlichen Nahverkehr gibt, die höchste Dichte an Self-Made-Millionären herrscht, wo jedem Einwohner umgerechnet ca. fünf Golfplätze an Grünflächen zur Verfügung stehen oder es 84.274,6 km Fußgängerwege gibt? Willkommen in West Perth! Zumindest analytisch gesehen ist der kleine Stadtteil
Los usuarios empresariales dependen de la disponibilidad de los datos, que estos sean confiables y que estén fácilmente disponibles cuando se necesita. Sin embargo, con datos dispersos en sistemas dispares y volúmenes de datos que aumentan rápidamente, la integración de estos no es una tarea fácil. Ante tal escenario,
Helmut Plinke explains why modernizing your data management is essential to supporting your analytics platform.
David Loshin discusses big data identity resolution in a programming and execution environment.
Many of the regulations coming into effect after 2010, are the result of the financial crisis that has significantly re-shaped the financial industry worldwide and especially in Europe. One of the major projects that has been undertaken by the statistics team of the ECB, launched in 2011, is the setup
Matthew Magne describes how SAS Data Quality can help you build a trusted data foundation, one stone at a time.
여러분은 ‘프로파일링(profiling)’하면 뭐가 제일 먼저 생각나나요? 아마 많은 분들이 범인을 추적하는 범죄 프로파일러(profiler)를 떠올릴 것 같은데요. 맞습니다. 프로파일링은 범죄 현장과 증거를 분석해 용의자의 범행 수법은 물론 성별, 나이, 습관, 성격, 직업 등을 추론하고 범인을 찾아내는 범죄 수사 기법 중 하나인데요. 최근 범죄 심리학을 다룬 드라마와 영화가 큰 인기를 끌며 대중에
IT organizations today are constantly challenged to do more with less. Reusing data processing jobs and employing best practices in monitoring the health of your data are proven ways to improve the productivity of data professionals. Dataflux Data Management Studio is a component of both the SAS Data Quality and
David Loshin says simple approaches to identity resolution may not scale on a big data platform as data volumes increase.
